1 / 26

CSCI-383

CSCI-383. Object-Oriented Programming & Design Lecture 2. Chapter 1 Thinking Object-Oriented. Why has OOP Remained Popular for so long?. OOP has been the dominant programming paradigm for more than twenty years. Why is it so popular? Proven record of success

sharonlyons
Download Presentation

CSCI-383

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. CSCI-383 Object-Oriented Programming & Design Lecture 2

  2. Chapter 1Thinking Object-Oriented

  3. Why has OOP Remained Popular for so long? • OOP has been the dominant programming paradigm for more than twenty years. Why is it so popular? • Proven record of success • Scales well from small problems to large • Nevertheless, programming is still a task that requires skill and learning

  4. Disclaimer • Effective use of object-oriented principles requires one to view the world in a new way • The use of an object oriented language does not make one an object oriented programmer “Fortran programs can be written in any language”

  5. A New Paradigm • Object-oriented programming is often described as a new paradigm. We start by considering the definition of this term: Paradigmn. A list of all the inflectional forms of a word taken as illustrative example of the conjugation or declension to which it belongs. An example or model. [Late Latein paradigma, from Greek paradeigma, modern paradeiknunai, to compare, exhibit.]

  6. Sapir-Whorf Hypothesis • In linguistics there is a hypothesis that the language in which an idea or thought is expressed colors or directs in a very emphatic manner that nature of the thought

  7. The SWH argues that we experience the world based on the words we have • In an experiment, people were asked to describe how many bands or stripes they saw in a rainbow • Since rainbows are a continuum of colors, no empirical stripes or bands • Nevertheless, people saw as many stripes or bands as their language possessed primary color words • Inuit language and snow, Arabic language and camels • Is it true that the way we think is completely determined by the language we use? This implies that: • The words we have determine the things we can know • If we have an experience, we are confined not just in our communication of it, but also in our knowledge of it, by the words we have

  8. Arguments against this hypothesis? • People usually have trouble expressing themselves and are aware that the language is not adequate for what they mean • “That’s not quite what I meant to say…” • This provides evidence that what is being thought is not a set of words because one can understand a concept without being able to express it in words • Truth probably somewhere in the middle, language may not complete determine but influences the way we think

  9. Sapir-Whorf Hypothesis (cont’d) • What in the world does this have to do with computer programming languages? • What is true of natural languages is even more true of artificial computer languages

  10. Example from Computer Languages • A student working in DNA research had the task of finding whether any pattern of length M (M fixed and small) is repeated in a given DNA sequence of length N (N very very large) ACTCGGATCTTGCATTTCGGCAATTGGACCCTGACTTGGCCA ...

  11. Example from Computer Languages • Wrote the simplest (and therefore, most efficient?) Fortran program: DO 10 I = 1, N-M DO 10 J = I+1, N-M FOUND = .TRUE. DO 20 K = 1, M 20 IF X[I+K-1] .NE. X[J+K-1] THEN FOUND = .FALSE. IF FOUND THEN ... 10 CONTINUE Took a depressingly long time. Asymptotic time complexity?

  12. A Better Solution • A friend writing in APL found a much better solution by rearranging the data and sorting • Reorganize in NxM matrix A C T C G G positions 1 to M C T C G G A positions 2 to M+1 T C G G A T positions 3 to M+2 C G G A T T positions 4 to M+3 G G A T T C positions 5 to M+4 G A T T C T positions 6 to M+5 . . . • Sort matrix on rows and look for equal adjacent rows Ran surprisingly quickly, thesis saved

  13. What lead to the discovery? • Why did the APL programmer find the better solution? • Fortran programmer was blinded by a culture that valued loops, simple programs. Fortran programmer thinks in terms of loops • Sorting is a built-in operation in APL, good programmers try to find novel uses for sorting. APL programmer thinks in terms of manipulating sequences; sort is built-in, loops do not exist • APL is not a “more efficient” language than Fortran • The fundamental point is that the language you speak leads you in one direction or another

  14. Rule du Jour If the only tool you have is a hammer, everything in the world looks like a nail.

  15. Church's Conjecture • But what about the Sapir-Whorf hypothesis, that says there are some thoughts you can express in one language that you cannot express in another? • In computation we have the following assertion: Church's Conjecture: Any computation for which there exists an effective procedure can be realized by a Turing machine language • Anything can be done in any language, but it may simply be easier or more efficient to use one language or another. Note that is almost directly opposite to the SWH • Would YOU want to write an event-driven GUI interface in Turing machine language? • Bottom line: Languages lead you, but do not prevent you from going anywhere you want

  16. Imperative Programming • So, what are the paradigms of programming? • Imperative programming is the “traditional” model of computation • State • Variables • Assignment • Loops • A processing unit is separate from memory, and “acts” upon memory

  17. Visualization of Imperative Programming

  18. Why Not Build a Program out of Computers? • Alan Kay thought about this conventional design of the computer, and asked why we constructed the whole out of pieces that were useless by themselves • Why not build a whole out of pieces that were similar at all levels of detail? (Think of fractals) • Idea: A program can be build out of little computing agents

  19. Recursive Design • The structure of the part mirrors the structure of the larger unit

  20. Kay's Description of Object-Oriented Programming • Object-oriented programming is based on the principle of recursive design • Everything is an object • Objects perform computation by making requests of each other through the passing of messages • Every object has it's own memory, which consists of other objects • Every object is an instance of a class. A class groups similar objects • The class is the repository for behavior associated with an object • Classes are organized into singly-rooted tree structure, called an inheritance hierarchy • We can illustrate these principles by considering how I go about solving a problem in real life

  21. Illustration of OOP Concepts -- Sending Flowers to a Friend • To illustrate the concepts of OOP in an easily understood framework, consider the problem of sending flowers to a friend who lives in a different city. Chris is sending flowers to Robin. • Chris can't deliver them directly. So Chris uses the services of the local Florist • Chris tells the Florist (named Fred) the address for Robin, how much to spend, and the type of flowers to send • Fred contacts a florist in Robins city, who arranges the flowers, then contacts a driver, who delivers the flowers • If we start to think about it, there may even be other people involved in this transaction. There is the flower grower, perhaps somebody in charge of arrangements, and so on

  22. Agents and Communities • Our first observation is that results are achieved through the interaction of agents, which we will call objects • Furthermore, any nontrivial activity requires the interaction of an entire community of objects working together • Each object has a part to play, a service they provide to the other members of the community

  23. Elements of OOP - Objects • So we have Kay's first principle • Everything is an object • Actions in OOP are performed by agents, called instances or objects • There are many agents working together in my scenario. We have Chris, Robin, the florist, the florist in Robins city, the driver, the flower arranger, and the grower. Each agent has a part to play, and the result is produced when all work together in the solution of a problem

  24. Elements of OOP - Messages • And principle number 2: • Objects perform computation by making requests of each other through the passing of messages • Actions in OOP are produced in response to requests for actions, called messages. An instance may accept a message, and in return will perform an action and return a value • To begin the process of sending the flowers, Chris gives a message to Fred. Fred in turn gives a message to the florist in Robins city, who gives another message to the driver, and so on

  25. Information Hiding • Notice that I, as a user of a service being provided by an object, need only know the name of the messages that the object will accept • I need not have any idea how the actions performed in response to my request will be carried out • Having accepted a message, an object is responsible for carrying it out

  26. Elements of OOP - Receivers • Messages differ from traditional function calls in two very important respects: • In a message there is a designated receiver that accepts the message • The interpretation of the message may be different, depending upon the receiver

More Related